Abstract

We propose a frequency-domain sparse iterative covariance-based estimation (FD-SPICE) approach for the high-resolution time delay estimation of spread spectrum signals. The conventional correlation method fails to resolve the signals in the case where they are spaced within a Rayleigh resolution limit and further processing should be applied to the correlation outputs in order to improve performance. SPICE is one of the most prominent candidates for further processing since it has various advantages over subspace-based approaches. SPICE is implemented normally in the time domain like other sparse signal reconstruction-based approaches. However, the time-domain SPICE (TD-SPICE) approach suffers from a severe performance degradation in coherent signal cases, as in direction-of-arrival estimation. We develop an FD-SPICE approach which makes use of the Fourier transform bins of the correlation output samples to form a sample covariance matrix. Numerical examples demonstrate the superiority of FD-SPICE over TD-SPICE, especially in coherent signal cases.

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